Postúlate en Kit Empleo: kitempleo.cl/empleo/1danrt

Blend is a premier AI services provider, dedicated to co‑creating meaningful impact for its clients through data science, AI, and technology.

Job Description

What is this position about?

- Validate data accuracy and ensure production readiness by working closely with the Data Engineering Manager and Analytics Engineering Lead across 18 data domains.
- Design and build a reconciliation framework to systematically compare legacy pipeline outputs against new pipeline outputs, identifying discrepancies and gaps.
- Execute structured acceptance testing for each pipeline prior to promotion to production environments.
- Validate identity resolution accuracy through rigorous analysis of match rates, false positives, and false negatives.
- Document end-to-end data lineage across all 18 domains to support auditability, transparency, and regulatory compliance.
- Build and maintain automated regression test suites to enable continuous quality assurance as pipelines evolve.

Qualifications

- Expert-level SQL skills, with demonstrated ability to write complex queries for data validation, profiling, and reconciliation at scale.
- Experience with data quality frameworks; preference for candidates with Great Expectations expertise.
- Proficiency in Python for scripting automated tests,



data profiling tasks, and quality checks.
- Strong background in data profiling techniques, including distribution analysis, completeness checks, and anomaly detection.
- Experience designing and executing test automation strategies in data or analytics engineering contexts.
- Ability to clearly document findings and communicate data quality issues to both technical and non‑technical stakeholders.

Languages

English: Advanced (required for effective communication with global teams).

Experience

3+ years of experience in Data Quality, QA, or Data Analysis roles, with proven ability to build reconciliation frameworks and execute end-to-end acceptance testing across complex data pipelines.

Benefits & Perks

- Learning opportunities: certifications in AWS, Databricks, and Snowflake; AI learning paths; access to Udemy Business; English lessons.
- Career development: mentorship programs and development plans.
- Celebrations: special day rewards for birthdays, work anniversaries, and personal milestones.
- Company‑provided equipment.
- Adaptable working options.
- Additional benefits vary by location (LATAM).

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Postúlate en Kit Empleo: kitempleo.cl/empleo/1danrt

📌 Data Quality QA Engineer — Flexible Work Options (Santiago)
🏢 Blend
📍 Santiago